MRC Human Genetics Unit, Medical Research Council, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, Scotland, United Kingdom.
G3 (Bethesda). 2012 Sep;2(9):1067-75. doi: 10.1534/g3.112.002618. Epub 2012 Sep 1.
Genome-wide association studies (GWAS) aim to detect single nucleotide polymorphisms (SNP) associated with trait variation. However, due to the large number of tests, standard analysis techniques impose highly stringent significance thresholds, leaving potentially associated SNPs undetected, and much of the trait genetic variation unexplained. Pathway- and network-based methodologies applied to GWAS aim to detect associations missed by standard single-marker approaches. The complex and non-random architecture of the genome makes it a challenge to derive an appropriate testing framework for such methodologies. We developed a rapid and simple permutation approach that uses GWAS SNP association results to establish the significance of pathway associations while accounting for the linkage disequilibrium structure of SNPs and the clustering of functionally related elements in the genome. All SNPs used in the GWAS are placed in a "circular genome" according to their location. Then the complete set of SNP association P values are permuted by rotation with respect to the genomic locations of the SNPs. Once these "simulated" P values are assigned, the joint gene P values are calculated using Fisher's combination test, and the association of pathways is tested using the hypergeometric test. The circular genomic permutation approach was applied to a human genome-wide association dataset. The data consists of 719 individuals from the ORCADES study genotyped for ~300,000 SNPs and measured for 51 traits ranging from physical to biochemical measurements. KEGG pathways (n = 225) were used as the sets of pathways to be tested. Our results demonstrate that the circular genomic permutations provide robust association P values. The non-permuted hypergeometric analysis generates ~1400 pathway-trait combination results with an association P value more significant than P ≤ 0.05, whereas applying circular genomic permutation reduces the number of significant results to a more credible 40% of that value. The circular permutation software ("genomicper") is available as an R package at http://cran.r-project.org/.
全基因组关联研究(GWAS)旨在检测与性状变异相关的单核苷酸多态性(SNP)。然而,由于测试数量众多,标准分析技术施加了非常严格的显著性阈值,导致潜在相关的 SNP 未被检测到,并且性状遗传变异的很大一部分未得到解释。应用于 GWAS 的基于途径和网络的方法旨在检测标准单标记方法错过的关联。基因组的复杂和非随机结构使得为这种方法开发适当的测试框架具有挑战性。我们开发了一种快速而简单的置换方法,该方法使用 GWAS SNP 关联结果来确定途径关联的显著性,同时考虑 SNP 的连锁不平衡结构和基因组中功能相关元件的聚类。GWAS 中使用的所有 SNP 根据其位置放置在“圆形基因组”中。然后,根据 SNP 的基因组位置旋转,对完整的 SNP 关联 P 值集进行置换。一旦分配了这些“模拟”P 值,就使用 Fisher 组合检验计算联合基因 P 值,并使用超几何检验检验途径的关联。圆形基因组置换方法应用于人类全基因组关联数据集。该数据由 ORCADES 研究中的 719 个人组成,这些人对大约 300,000 个 SNP 进行了基因分型,并对 51 个性状进行了测量,这些性状从物理到生化测量不等。KEGG 途径(n = 225)被用作要测试的途径集。我们的结果表明,圆形基因组置换提供了稳健的关联 P 值。未经置换的超几何分析生成了约 1400 个具有关联 P 值大于 P ≤ 0.05 的途径-性状组合结果,而应用圆形基因组置换将显著结果的数量减少到更可信的值的 40%。圆形置换软件(“genomicper”)可作为 R 包在 http://cran.r-project.org/ 上获得。